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Time For Website Nip Tuck
We have been working with a very prominent plastic surgery clinic that has successfully delivered excellent results to its clients for over 15 years.
Every prominent business must adapt to and understand advents in technology and online marketing.
This is no different for plastic surgeons as they receive a vast amount of their leads through online sources, surveys, videos, and informational posts educating their prospective clients on various procedures.
For this particular study, we performed a Competitor Gap Analysis between our client's website and three of their main competitors.
The idea is to find all of the verticals that their competition is ranking for, what they are doing right and how to reverse engineer this to optimize their business.
Due to a non-disclosure agreement, we will not share the actual URLs used.
Nevertheless, we can discuss the results and our findings, which is the main value addition to our readers.
Close To Perfect Clusters
The results from this Gap Analysis unraveled many exciting ideas around content to capture our client's target audience.
The most intriguing part of this study is that almost all the clusters we produced intuitively make sense!
Upon our manual inspection of the results, all keywords were thematically related to the parent cluster's intent.
This is evidence that our approach works best when the keywords we are trying to group are thematically relevant.
It is very challenging to derive groupings for unrelated keywords that don't share many SERPs.
By using direct competitors, we can discover a pure set of keywords in our niche.
We just need to properly "piggy-back" on Google's magnificent NLP efforts to cluster the intent and the topical relevancy of similar queries. After utilizing our smart filtering algorithm to clear all junk keywords, we ended up with 320 keywords.
Our Smart Filtering Algorithm© analyzes multiple features such as low impression volume, high frequency of authority sites in the results, low-value words in the keyword, etc. to determine if the keyword is worth passing to the final dataset.
To "Lipo" Or Not To "Lipo"?
Our client was quite happy with the list of 320 keywords we presented to them, but our job didn't end there.
In particular, we had to answer more questions, such as:
What cosmetic surgery should I focus on first, and why?
Should I create separate posts for 'How Much Is Gyno Surgery' and 'Gyno Surgery Cost' or put them on the same page?
WHY choose silo 'Men Chest Reduction' over silo 'Men Liposuction'?
Keyword Matchmaking From The "Google Heavens"
Keyword Cupid is here to help you answer all of your questions with only one objective;
To help you rank in the eyes of Google.
Our hypothesis is simple...
then "Man Boob" and "Gynecomastia" must be related.
- Keyword Cupid
We don't care to answer why or how they are related, nor are we trying to reverse engineer the NLP algorithm that produces that association.
Our objective is to place the keywords that Google associates with each other on the same page/silo of their site.
This way, we can speak the same language as the Google NLP algorithm.
TLDR: We utilize state of the art machine learning models to cluster keywords that have the highest overlap in SERPs, using an exponentially weighted curve to place more importance on results from first pages.
Enough about that, let's jump to the results, shall we?
Time to "Lift" These Webpages
Keyword Cupid's matchmaking process clusters keywords that have the highest overlap in their search engine rankings.
In the following two images, you can see that "gynecomastia surgery price" and "average cost of gynecomastia surgery" are placed within the same cluster because they have 8/10 matching results on page 1 of Google.
Our algorithm analyzes up to the first ten pages of each keyword to calculate the SERP overlaps.
We automatically aggregate the impressions and difficulty of the children in the parent node to calculate the importance of each cluster.
In particular, the parent level cluster that captures keywords related to "how much is gyno surgery" contains keywords that have a total impression volume of 11k per month with an average difficulty of about 5/100.
Note that we show only the top 10 SERPs per keyword in the interactive graph for usability purposes.
Our algorithms use an exponentially weighted curve to consider 50+ results for each keyword.
If two keywords belong in the same cluster and they don't happen to overlap on the first page, it's because they have commonalities in subsequent pages.
Beyond Long Tails and LSI
A basic keyword research approach would rely on the lexicographical distance of words to assess keyword similarity.
A more advanced approach would use natural language processing methodologies and latent semantic indexing and ontology structures to find similar keywords that have been identified in large corpora through algorithms like Word2Vec or Bert.
That approach would hopefully recommend "man boobs" as another version of "man breasts".
Our approach goes one step further also to capture the intent of each SERP.
If we pay very close attention to the images below, we can see that the keyword "man boobs" appears to have more informational intent, i.e. "man boob pics", "pictures of man boobs", etc.
On the contrary, when examining a separate cluster of "men chest reduction" which revolves around the surgical procedure, medical terms like "gynecomastia surgery" and "male breast surgery" appear.
We interpret this as people searching for more "layman" terms when exploring what things look like and proper terminology when things get more serious. It's time to investigate the surgical option.
Such a finding is important when crafting our calls to action.
We now know that potential leads are more susceptible to becoming clients if we use the right terminology.
Flattening The Learning Curve
Have you ever wanted to enter a niche with a lot of domain-specific knowledge?
Ample curiosity is a tool that transcends SEO and a good-old Google search will always be a great tool to learn new things.
However, is there a better way to learn?
We advocate there is!
Take, for example, the keyword "erbium laser resurfacing"...
If you are as oblivious to the practice of medicine as we are, you might be wondering if this is even English.
If you do a quick Google search, you will find that erbium laser resurfacing removes surface-level and moderately deep lines and wrinkles.
Alternatively, look at the clusters that Keyword Cupid produces.
The image below explains that "erbium laser resurfacing" appears to be very tightly (no pun intended) related to operations tightening the female reproductive organs.
This very specialized surgery is placed automatically in the same cluster as "how to tighten labia", "floppy vaginas" and so forth means that reverse-engineering the Google results works and even captures the intent of each query.
It is important to note that this approach will always adapt to the search intents, as we pull live search results at the moment of the query.
This way, we guarantee that the clusters you get are absolutely relevant to the present status-quo.
From this client case study, we have learned a great deal about not only the association of keywords but search intent.
This report provides anyone who wants to rank in the plastic surgery niche with actionable steps to attract interested customers.
From our mindmap you can make informed decisions on the best keywords to target as well as how to structure them within your site.
Our clustering algorithm creates the silo structure automatically and aggregates the total impression volume and average keyword difficulty for each grouping.
This way, you can select which hubs or pages to prioritize and instruct your content writers to use those keywords appropriately.
The results of this study help us better understand the benefits of using Keyword Cupid, and identify best practices to yield the most informative results.
As we discussed above, our clusters offered valuable insight to distinguish intent between seemingly similar keywords.
For example, the terms "man boobs" and "gynecomastia" technically have the same meaning.
However, "man boobs" was associated with keywords centered around searching pictures and photos.
Thus we inferred that this terminology implies informational intent.
On the contrary, "gynecomastia" appeared in keywords about surgical operations like gynecomastia surgery, liposuction, etc.
Therefore, this terminology is likely used prominently in later phases of the buying cycle.
In addition to distinguishing intent, Keyword Cupid helped us understand niche specific terminology that a non-medical person would likely be confused by. For example, although erbium laser resurfacing is primarily known for removing fine lines and wrinkles, it is also a state-of-the-art method for nonsurgical vaginal rejuvenation, as you can see in this medical journal.
Although we are not doctors and don't spend our time reading medical journals, we discovered this because our clustering algorithm placed "erbium laser resurfacing" under the centroid node "saggy labia".
Finally, this case study serves as clear evidence that the best results come from a keyword list that is thematically related.
Such a list is a result of the user submitting URLs that are direct competitors of their target site, and are ranking for keywords that they are after.
Generic sites such as Forbes or other large news portals will yield poor results as they rank for a plethora of possibly unrelated keywords.
This variability will distort the homogeneity of the resulting clusters.
In other words, choose your sites diligently, and Keyword Cupid will reward you.
Spread The Love To YOUR Project
Are you interested in applying our methodologies to your own project?
Do you want to quickly get a recipe of how to target your competition and fill in the missing gaps in your content strategy?
We are ready to help!
Just point our cupid arrows in the right direction!